Advances in computing hardware and software have facilitated decentralization of computing tasks to increasing numbers of networked service applications, servers, and repositories, which collectively (and conceptually) has become known as “the cloud” or “cloud computing,” which includes implementations of “virtual private cloud” (“VPC”). As demand for cloud-based services increases, requirements to facilitate data connectivity increases exponentially among different applications residing on different computing hardware platforms in different networks. Consequently, numerous application programming interfaces (“APIs”) have are being developed to provide data-interpretive communication conduits through which to exchange data and instructions among disparate operating systems, applications, and computing devices. Many different approaches to create APIs have led to the creation and use of various ad hoc and non-standard APIs, most of which are generally created for specific or one-time use and not well-suited for reuse or adoption.
Further, principles of designing and developing APIs have increasingly implemented the use of “microservices” architectures and/or “containerization” techniques (e.g., encapsulating an API in a software-based container to operate in its own environment). For example, APIs developed consistent with a microservice architecture may typically be enterprise-focused, or business-oriented to enhance productivity of an organization. APIs developed in accordance with a microservice architecture is intended to facilitate development, deployment, and management of services independently, with each service being developed by a relatively smaller number of developers in contrast to developing APIs as a monolithic application.
However, there are drawbacks to developing APIs as distributed microservices. For example, different development teams may develop similar API functionalities that are usually disposed in isolated, or “siloed,” repositories, whereby discovery of similar or common API functionalities by other developers may be difficult. Further, each of the different teams of developers typically maintains documentation of API design files and functionalities for the APIs for which they are responsible. Generally, however, documentation for APIs in an enterprise or organization are commonly maintained in balkanized computing systems and data storage repositories (e.g., in fragmented repositories). Usually, developers of separately-developed APIs may conventionally create separate web pages that may provide API documentation for the APIs they developed. However, such API documents are implemented in isolation from other web-based API documents, whereby separate web pages direct to each API may omit information that might be common to other APIs documented in other web pages. Knowledge of each functionality and type of API in an organization is further frustrated by rapid scaling and complexity in the increasing number of independent versioned APIs (e.g., enterprises may develop hundreds to hundreds of thousands of API design files, versions, API data components, etc.). Also, accessibility of each of the distributed services and/or API design files stored in multiple repositories may operate independently, and, as such, interoperability of a subset of API data components may be susceptible to downtime or outages. Hence, newly designed APIs based on inaccessible API data may affect (e.g., delay) development of APIs in an organization.
Thus, what is needed is a solution for facilitating techniques to analyze, identify, and search over distinctive repositories to, among other things, enhance reusability of application interface data components to reduce consumption of computational resources as well as API development efforts and time, without the limitations of conventional techniques.